Phytoplankton adaptation in ecosystem models.
Adaptive evolution
Individual based model (IBM)
Multi-compartment model (MCM)
NPZD-Type model
Thermal adaptation
Trait diffusion model
Journal
Journal of theoretical biology
ISSN: 1095-8541
Titre abrégé: J Theor Biol
Pays: England
ID NLM: 0376342
Informations de publication
Date de publication:
07 05 2019
07 05 2019
Historique:
received:
27
09
2018
revised:
03
12
2018
accepted:
21
01
2019
pubmed:
24
2
2019
medline:
10
7
2020
entrez:
24
2
2019
Statut:
ppublish
Résumé
We compare two different approaches to model adaptation of phytoplankton through trait value changes. Both consider mutation and selection (MuSe) but differ with respect to the underlying conceptual framework. The first one (MuSe-IBM) explicitly considers a population of individuals that are subject to random mutation during cell division. The second is a deterministic multi-compartment model (MuSe-MCM) that considers numerous genotypes of the population and where mutations are treated as a transfer of biomass between neighboring genotypes (i.e., a diffusion of characteristics in trait space). Focusing on the adaptation of optimal temperature, we show model results for different scenarios: a sudden change in environmental temperature, a seasonal variation and high frequency fluctuations. In addition, we investigate the effect of different shapes of thermal reaction norms as well as the role of alternating growth and resting phases on the adaptation process. For all cases, the differences between MuSe-IBM and MuSe-MCM are found to be negligible. Both models produce a number of well-known and plausible features. While the IBM has the advantage of including more mechanistic (i.e., probabilistic) processes, the MCM is much less computationally demanding and therefore suitable for implementation in three-dimensional ecosystem models.
Identifiants
pubmed: 30796940
pii: S0022-5193(19)30033-5
doi: 10.1016/j.jtbi.2019.01.041
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
60-71Informations de copyright
Copyright © 2019 Elsevier Ltd. All rights reserved.